2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting

My APS/URSI 2019 Schedule

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Paper:	MO-SP.1P.3
Session:	Application of Machine/Deep Learning and Uncertainty Quantification Techniques in Computational Electromagnetics
Session Time:	Monday, July 8, 13:20 - 17:00
Presentation Time:	Monday, July 8, 14:00 - 14:20
Presentation:	Special Session Oral
Paper Title:	Fast Surrogate Model-Assisted Uncertainty Quantification via Quantized Tensor Train Decompositions
Authors:	Luis Gomez, Duke University School of Medicine, United States; Abdulkadir Yucel, Nanyang Technological University, Singapore; Weitian Sheng, Cadence Design Systems, United States; Eric Michielssen, University of Michigan, United States